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Houston Technology Center
    Tech Connection
Mark Kerzner - serial software
entrepreneur, inventor, scientist,
author
Paula DeWitte - data scientist,
lawyer, eDiscovery
Hartley Singer - finance captain
Ben Turin – lawyer, startup
architect
Problem
    • Exponential growth
      in data
    • Poorly processed
    • Badly understood
    • eDiscovery a
      burden

3
Solution
    • Distill and prepare the data
    • Classify and categorize it
    • Apply knowledge-based rules to
      support client’s claims

4
Benefits
    • Scalable
    • Good price/performance ratio
    • Pay-as-you-go model
    • You control your own data



5
Vision
• Legal
• Compliance
• Data governance




6

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SHMcloud vision

  • 1. Houston Technology Center Tech Connection
  • 2. Mark Kerzner - serial software entrepreneur, inventor, scientist, author Paula DeWitte - data scientist, lawyer, eDiscovery Hartley Singer - finance captain Ben Turin – lawyer, startup architect
  • 3. Problem • Exponential growth in data • Poorly processed • Badly understood • eDiscovery a burden 3
  • 4. Solution • Distill and prepare the data • Classify and categorize it • Apply knowledge-based rules to support client’s claims 4
  • 5. Benefits • Scalable • Good price/performance ratio • Pay-as-you-go model • You control your own data 5

Notas del editor

  1. I am Mark Kerzner, etc. etcSHMsoft is a technology firm specializing in Big Data and Hadoop.We have created award-winning software for eDiscovery, which is essentially enterprise search for lawyers.eDiscovery is a $4B market, steadily growing at 15% per year
  2. My story began a few years ago when, after the sale of an oil exploration software I’ve created, I started learning lawThis is the third eDiscovery system I have architected, and on this journey I am accompanied by a great team
  3. There is a lot of data in the legal worldIt is poorly processedIt is badly understoodCompanies and their Lawyers consider eDiscovery a burden. [talk a bit about the typical cost]Our winning mindset:We analyze all available data using cluster-based computingWe use extremely smart analytics to understand what the documents are sayingThe computers use all available case law information and teach us the best arguments to useThis becomes a powerful weapon in the arsenal
  4. First we distill the large amount of data and prepare it for smart analytics; for example, we can process all of Enron data in 1 hour on a 50-node cluster.Then we classify and categorize the data into precisely defined groups and concepts.Finally, we apply the knowledge obtained from all other sources to our data, to find the documents and the arguments that support the winning claims.
  5. The LegalTech is going in NY, but we have the record number of companies contact us for evaluation
  6. The vision for this technology: expand the technology to more areas Legal Compliance Data governance Bioinformatics Oil & GasAll these areas are on the verge of a Big Data revolution and we can help them to ride this wave.